code: def _make_schema_from_config(
      config: distribution_validator_pb2.DistributionValidatorConfig,
      statistics_list: statistics_pb2.DatasetFeatureStatisticsList,
  ) -> schema_pb2.Schema:
      """Converts a config to a schema that can be used for data validation."""
      schema = tfdv.infer_schema(statistics_list)
      for feature in config.default_slice_config.feature:
          try:
              schema_feature = schema_util.get_feature(
                  schema, path.FeaturePath.from_proto(feature.path)
              )
          except ValueError:
              # Statistics could be missing for features in the config in which case
              # they will not be present in the schema. Just continue; an anomaly will
              # be raised for such features in the step that looks for missing
              # comparisons in the result.
              pass
          else:
              schema_feature.drift_comparator.CopyFrom(
                  feature.distribution_comparator
              )
      if config.default_slice_config.HasField(
          "num_examples_comparator"
      ):
          schema.dataset_constraints.num_examples_drift_comparator.CopyFrom(
              config.default_slice_config.num_examples_comparator
          )
      return schema
  
imports: import os
  from typing import Any, Dict
  from absl import logging
  import tensorflow_data_validation
  from tensorflow_data_validation.utils import path
  from tensorflow_data_validation.utils import schema_util
  from tfx import types
  from tfx.components.statistics_gen import stats_artifact_utils
  from tfx.dsl.components.base import base_executor
  from tfx.orchestration.experimental.core import component_generated_alert_pb2
  from tfx.orchestration.experimental.core import constants
  from tfx.proto import distribution_validator_pb2
  from tfx.proto.orchestration import execution_result_pb2
  from tfx.types import artifact_utils
  from tfx.types import standard_component_specs
  from tfx.utils import json_utils
  from tfx.utils import monitoring_utils
  from tfx.utils import writer_utils
  from google.protobuf import any_pb2
  from tensorflow_metadata.proto.v0 import anomalies_pb2
  from tensorflow_metadata.proto.v0 import schema_pb2
  from tensorflow_metadata.proto.v0 import statistics_pb2
label_desc: Use image node_id 2 for calling a global function with example usage: _make_schema_from_config(config, statistics_list) and returns: schema